The present invention relates to computational processing. More particularly, the present invention provides amorphous computing systems and methods for using such to perform complex computational processing. Such complex processing can reduce a dataset to a user desirable form. As just one example, the dataset can be a group of seismic data that is reduced to form a three-dimensional image of a geologic formation. Other datasets can also be reduced.
The seismic processing industry is involved in processing large amounts of seismic data using very complex algorithms. This is especially true for imaging algorithms that use the majority of the compute power in this industry. Such processing has historically involved the use of expensive supercomputers, or high end workstations. As an example, the amounts of data involved and the complexity of the algorithms often requires weeks of processing time to create an image of a geologic structure. To reduce processing costs, the seismic processing industry has been experimenting with the use of low cost computers as its main processing engines. Using such an approach, as many as 10,000 or more low cost computers can be grouped to perform a single computation. However, because of the nature of the low cost computers, the devices comprising the low cost computers, and/or the means for grouping the low cost computers, it has been difficult to achieve more than approximately twenty percent of the computational capacity included in the low cost computers. Further, managing computational tasks operating on so many low cost computers presents a significant management responsibility.
Thus, there exists a need in the art to provide advanced systems and methods for computational processing. As will be appreciated from the following disclosure, the systems and methods according to the present invention address these, and a number of other problems related to processing.